GPS
The Global Positioning System (GPS) is a space-based satellite navigation system that provides location and time information in all weather conditions, anywhere on or near the Earth where there is an unobstructed line of sight to four or more GPS satellites. The system provides critical capabilities to military, civil and commercial users around the world. It is maintained by the United States government and is freely accessible to anyone with a GPS receiver.
The GPS project was developed in 1973 to overcome the limitations of previous navigation systems, integrating ideas from several predecessors, including a number of classified engineering design studies from the 1960s. GPS was created and realized by the U.S. Department of Defense (DoD) and was originally run with 24 satellites. It became fully operational in 1995.
Future aircraft will operate for long durations (from tens of minutes to several hours) at supersonic speeds (Mach 3 to Mach 5) and altitudes of 70,000 feet above ground level. There exists a strong possibility that such vehicles will not be able to rely upon GPS for the entire flight path. In some situations GPS may not be available. It can be jammed or interfered with to provide false information.
IMUs
An Inertial Measurement Unit (IMU) can mitigate the effects of GPS denial. However, gyro errors (attitude), accelerometer errors (position and velocity), and the “cross product” of acceleration and attitude errors accumulate over time. Consequently, the IMU precision can drift outside mission required accuracy. A star tracker potentially can provide periodic updates to bound position and attitude errors in the IMU. However, a conventional star tracker on a moving platform has a limitation. It can determine precision attitude fix (pitch, roll and yaw) by imaging two, or more, bright starts separated by a large angular distance. It cannot however determine position fix with respect to terrestrial reference frame. The latter is because a local vertical reference is required to determine position fix from the star measurements. Since neither an accelerometer nor a tilt meter can discriminate between gravity force and acceleration, measurements of the local vertical on a moving platform are very difficult. This places a fundamental limitation on utility of conventional star trackers for High Mach High Altitude (HMHA) air vehicles and Unmanned Air Vehicles (UAV). The IMU is the main component of Inertial Navigation S stems (INSs).
INSs
At low terrain-following altitudes, a high quality Inertial Navigation System (INS) coupled with a radar altimeter, radar sensor, or Doppler navigation sensor is used by long-range cruise missiles and combat aircrafts. However, at high altitudes, active RF and optical sensors are susceptible to detection by enemy defense systems. This precludes the use of active RF and optical sensors. On the other hand, at high altitudes, optical imaging of the terrain features cannot be used for navigation due to cloud cover over long ranges. This suggests that a non-conventional approach must be developed for GPS denied navigation of high altitude air vehicles.
Inertial navigation systems play a major role in mitigating the effects of GPS denial. The IMU is initialized at a launcher. Then using a continuous, rapid series of gyro and accelerometer measurements, the IMU computes the air vehicle's instantaneous position, velocity, and attitude at any given later time. However, gyro error (attitude), accelerometer error (position and velocity), and the “cross product” of acceleration and attitude errors accumulate over time. Depending on the precision of the IMU, this “cross product” can accumulate at different rates. To provide accurate position estimates, periodic IMU updates from an external system are required in order to correct for position and attitude drifts, as well as “cross product” of acceleration and attitude error. A passive optical star tracker can potentially provide those periodic updates needed to correct the IMU navigation errors. Celestial-inertial navigation systems have been successfully used on a small number of aircrafts (SR-71, U-2, and B-2 and B-58 bombers).
Kalman Filters
The Kalman filter is an algorithm that uses a series of measurements from different sensors observed over time, containing noise (random variations) and other inaccuracies, and produces estimates of unknown variables that tend to be more precise than those based on a single measurement alone. More formally, the Kalman filter operates recursively on streams of noisy input data to produce a statistically optimal estimate of the underlying system state. A common application for the Kalman filter is for guidance, navigation and control of vehicles, particularly aircraft and spacecraft. The algorithm works in a two-step process. In the prediction step, the Kalman filter produces estimates of the current state variables, along with their uncertainties. Once the outcome of the next measurement (necessarily corrupted with some amount of error, including random noise) is observed, these estimates are updated using a weighted average, with more weight being given to estimates with higher certainty. Because of the algorithm's recursive nature, it can run in real time using only the present input measurements and the previously calculated state and its uncertainty matrix; no additional past information is required.
Applicants and their fellow workers have developed and field demonstrated an Automated Celestial Navigation System for navigation of surface ships. See U.S. Pat. No. 7,447,591, issued Nov. 4, 2008. This invention utilizes a large infrared telescope to image stars even during daylight hours. This system however requires knowledge of the gravity vector which the Applicants obtained from an inclinometer. Under a follow-on contract funded by the National Geospatial Intelligence Agency (NGA), Applicant's employer built an Electronic Replacement for Geodetic Astrolabe for precision mapping of the Earth gravity field. This sensor determined the deflections of vertical of the gravity field with precision of 1 grad using star measurements. The sensor was also a precision navigator for terrestrial applications with position accuracy of 6 m. In both cases, a precision inclinometer, or tilt meter, was used to measure the local vertical. This measurement was used to convert the observer position in a celestial reference frame, determined from star angular measurements, into a geo-position in a terrestrial reference frame, longitude and latitude. However, on a moving platform, the inclinometer cannot discriminate a gravity field from acceleration, and thus cannot be used to measure local vertical.
What is needed is a new approach, independent of the local vertical, for measurements on a moving platform to provide periodic updates to correct navigation errors in the INS.